1. Field of Invention
The present invention is directed to wireless communications networks, and more particularly, to a system that automatically determines the manner in which available capital should be spent in order to achieve a given level of performance in a wireless network.
2. Description of Related Art
As wireless network subscriber bases grow, decisions must be made as to what changes need to be made to the network in order to meet growing demands. Changes to the network may include adding new equipment, such as a new cell site, for example, or making modifications to existing equipment, such as, for example, changing the azimuth of an antenna of an existing cell site. The cost of making a change will vary depending on the type of change that is made. For example, adding a new cell site may cost hundreds of thousands of dollars, whereas changing the azimuth of an existing cell site antenna may cost a few thousand dollars. Therefore, it is extremely important that the solution that is implemented be a cost effective solution and that it enable a desired or necessary level of network quality performance to be achieved.
Voice channel forecast (VCF) tools are used by network designers to project, or forecast, increases in network traffic that will occur as a result of increases in the number of subscribers using the network. The VCF tool is provided with financial information, such as subscriber sales information, for example, and network capacity information, such as the number of available channels of a cell site, for example. Based on this information, the VCF tool forecasts increases in network traffic for each sector of the network over a given period of time and determines whether or not the increases will exceed network capacity. Using these forecasts, designers use other tools to determine how the network can be modified or expanded to meet the forecasted increases in network traffic.
A tool known as an automatic cell planning (ACP) analyzer receives as its input a network traffic forecast generated by the VCF tool and an existing network configuration. The ACP analyzer processes this information and outputs the locations of any additional cell sites that need to be added to the network to meet the forecasted increased traffic demands. If the VCF tool indicates that network capacity for a given network sector will be exceeded by a particular amount, the ACP analyzer will determine the number of cell sites that need to be added to meet the increased demand. The ACP analyzer also determines whether other types of cell site modifications need to be made such as, for example, an antenna type change, an antenna orientation change, an antenna height change, an antenna tilt change, cell site relocation, sector addition, power change, etc.
A tool known as an automatic frequency planning (AFP) analyzer receives as its input a traffic forecast and an existing network configuration and outputs the number of additional frequencies that will need to be added to the network to meet the forecasted increased traffic demands. If the VCF tool indicates that network capacity for a given sector will be exceeded by a particular amount, the AFP analyzer will determine the number of channels that need to be added to a cell site to meet the increased demand. The ACP and AFP analyzers can be run simultaneously to create multiple combinations of changes.
Network designers also look at the costs associated with making an expansion or modification to the network. Typically, a certain amount of capital is available to make expansions or modifications and the designer must take this into account when determining what changes will be made. The cost information is available to the designers, so they know the costs associated with making various types of changes to the network. For example, if a designer can meet the increased traffic demand by adding additional channels rather than adding an additional cell site, the designer will often opt for the less expensive solution of adding more channels. Erlang constraints limit the number of frequencies, and thus the number of channels, that can be carried by a cell site. Such constraints may make it necessary to add another cell site as opposed to increasing the number of channels of the cell site. In addition, quality of service (QoS) is taken into account to ensure that whatever changes are made to the network enable the network to achieve a particular quality of service. For example, a QoS metric known as grade of service (GOS) is a measurement of the number of blocked calls that will be tolerated. The network designer may determine that adding additional channels rather than adding another cell site will result in an intolerable number of calls being blocked, and thus opt for the more expensive solution of adding another cell site.
A tool known as a QoS analyzer analyzes a network configuration generated by the ACP and/or AFP analyzers and predicts the network performance of the new network configuration. A tool known as a key performance indicators (KPI) analyzer works in conjunction with the QoS analyzer. The KPIs are metrics utilized to measure system performance. When the QoS analyzer predicts network performance, the KPI analyzer measures the predicted performance against the KPIs to determine the level of network quality performance.
Although tools such as those mentioned above are available to help network designers decide which solutions are the most cost effective, the decision making process is difficult because it is a subjective process that requires the designer to look at many different variables simultaneously and determine which solutions achieve the desired level of performance and are the most cost effective. As a result, the process of making these choices is prone to human error, and the solutions that are implemented may not be cost effective and/or may not achieve the best level of performance.
A need exists for a system that automates the process of determining the types of changes that can be made to a network to achieve a desired level of performance and, of those solutions, which are the most cost effective. By automating this process, it is possible to eliminate problems associated with implementing solutions that do not achieve the desired level of network quality performance and/or that are not cost effective.